Reindex does not attempt to set up the destination index. It does
not copy the settings of the source index. You should set up the destination
index prior to running a _reindex action, including setting up mappings, shard
counts, replicas, etc.

The most basic form of _reindex just copies documents from one index to another.
This will copy documents from the twitter index into the new_twitter index:

Just like _update_by_query, _reindex gets a
snapshot of the source index but its target must be a different index so
version conflicts are unlikely. The dest element can be configured like the
index API to control optimistic concurrency control. Just leaving out
version_type (as above) or setting it to internal will cause Elasticsearch
to blindly dump documents into the target, overwriting any that happen to have
the same type and id:

Setting version_type to external will cause Elasticsearch to preserve the
version from the source, create any documents that are missing, and update
any documents that have an older version in the destination index than they do
in the source index:

index and type in source can both be lists, allowing you to copy from
lots of sources in one request. This will copy documents from the _doc and
post types in the twitter and blog index. The copied documents would include the
post type in the twitter index and the _doc type in the blog index. For more
specific parameters, you can use query.

The Reindex API makes no effort to handle ID collisions. For such issues, the target index
will remain valid, but it’s not easy to predict which document will survive because
the iteration order isn’t well defined.

If you want a particular set of documents from the twitter index you’ll
need to use sort. Sorting makes the scroll less efficient but in some contexts
it’s worth it. If possible, prefer a more selective query to size and sort.
This will copy 10000 documents from twitter into new_twitter:

The source section supports all the elements that are supported in a
search request. For instance, only a subset of the
fields from the original documents can be reindexed using source filtering
as follows:

Like _update_by_query, _reindex supports a script that modifies the
document. Unlike _update_by_query, the script is allowed to modify the
document’s metadata. This example bumps the version of the source document:

Just as in _update_by_query, you can set ctx.op to change the
operation that is executed on the destination index:

noop

Set ctx.op = "noop" if your script decides that the document doesn’t have
to be indexed in the destination index. This no operation will be reported
in the noop counter in the response body.

delete

Set ctx.op = "delete" if your script decides that the document must be
deleted from the destination index. The deletion will be reported in the
deleted counter in the response body.

Setting ctx.op to anything else will return an error, as will setting any
other field in ctx.

Think of the possibilities! Just be careful; you are able to
change:

_id

_type

_index

_version

_routing

Setting _version to null or clearing it from the ctx map is just like not
sending the version in an indexing request; it will cause the document to be
overwritten in the target index regardless of the version on the target or the
version type you use in the _reindex request.

By default if _reindex sees a document with routing then the routing is
preserved unless it’s changed by the script. You can set routing on the
dest request to change this:

keep

Sets the routing on the bulk request sent for each match to the routing on
the match. This is the default value.

discard

Sets the routing on the bulk request sent for each match to null.

=<some text>

Sets the routing on the bulk request sent for each match to all text after
the =.

For example, you can use the following request to copy all documents from
the source index with the company name cat into the dest index with
routing set to cat.

The host parameter must contain a scheme, host, and port (e.g.
https://otherhost:9200). The username and password parameters are
optional, and when they are present _reindex will connect to the remote
Elasticsearch node using basic auth. Be sure to use https when using
basic auth or the password will be sent in plain text.

Remote hosts have to be explicitly whitelisted in elasticsearch.yml using the
reindex.remote.whitelist property. It can be set to a comma delimited list
of allowed remote host and port combinations (e.g.
otherhost:9200, another:9200, 127.0.10.*:9200, localhost:*). Scheme is
ignored by the whitelist - only host and port are used, for example:

The whitelist must be configured on any nodes that will coordinate the reindex.

This feature should work with remote clusters of any version of Elasticsearch
you are likely to find. This should allow you to upgrade from any version of
Elasticsearch to the current version by reindexing from a cluster of the old
version.

To enable queries sent to older versions of Elasticsearch the query parameter
is sent directly to the remote host without validation or modification.

Reindexing from a remote server uses an on-heap buffer that defaults to a
maximum size of 100mb. If the remote index includes very large documents you’ll
need to use a smaller batch size. The example below sets the batch size to 10
which is very, very small.

It is also possible to set the socket read timeout on the remote connection
with the socket_timeout field and the connection timeout with the
connect_timeout field. Both default to 30 seconds. This example
sets the socket read timeout to one minute and the connection timeout to 10
seconds:

In addition to the standard parameters like pretty, the Reindex API also
supports refresh, wait_for_completion, wait_for_active_shards, timeout,
scroll and requests_per_second.

Sending the refresh url parameter will cause all indexes to which the request
wrote to be refreshed. This is different than the Index API’s refresh
parameter which causes just the shard that received the new data to be refreshed.

If the request contains wait_for_completion=false then Elasticsearch will
perform some preflight checks, launch the request, and then return a task
which can be used with Tasks APIs
to cancel or get the status of the task. Elasticsearch will also create a
record of this task as a document at .tasks/task/${taskId}. This is yours
to keep or remove as you see fit. When you are done with it, delete it so
Elasticsearch can reclaim the space it uses.

wait_for_active_shards controls how many copies of a shard must be active
before proceeding with the reindexing. See here
for details. timeout controls how long each write request waits for unavailable
shards to become available. Both work exactly how they work in the
Bulk API. As _reindex uses scroll search, you can also specify
the scroll parameter to control how long it keeps the "search context" alive,
(e.g. ?scroll=10m). The default value is 5 minutes.

requests_per_second can be set to any positive decimal number (1.4, 6,
1000, etc) and throttles the rate at which _reindex issues batches of index
operations by padding each batch with a wait time. The throttling can be
disabled by setting requests_per_second to -1.

The throttling is done by waiting between batches so that the scroll which _reindex
uses internally can be given a timeout that takes into account the padding.
The padding time is the difference between the batch size divided by the
requests_per_second and the time spent writing. By default the batch size is
1000, so if the requests_per_second is set to 500:

Since the batch is issued as a single _bulk request, large batch sizes will
cause Elasticsearch to create many requests and then wait for a while before
starting the next set. This is "bursty" instead of "smooth". The default value is -1.

This flag is set to true if any of the requests executed during the
reindex timed out.

total

The number of documents that were successfully processed.

updated

The number of documents that were successfully updated.

created

The number of documents that were successfully created.

deleted

The number of documents that were successfully deleted.

batches

The number of scroll responses pulled back by the reindex.

noops

The number of documents that were ignored because the script used for
the reindex returned a noop value for ctx.op.

version_conflicts

The number of version conflicts that reindex hit.

retries

The number of retries attempted by reindex. bulk is the number of bulk
actions retried and search is the number of search actions retried.

throttled_millis

Number of milliseconds the request slept to conform to requests_per_second.

requests_per_second

The number of requests per second effectively executed during the reindex.

throttled_until_millis

This field should always be equal to zero in a _delete_by_query response. It only
has meaning when using the Task API, where it
indicates the next time (in milliseconds since epoch) a throttled request will be
executed again in order to conform to requests_per_second.

failures

Array of failures if there were any unrecoverable errors during the process. If
this is non-empty then the request aborted because of those failures. Reindex
is implemented using batches and any failure causes the entire process to abort
but all failures in the current batch are collected into the array. You can use
the conflicts option to prevent reindex from aborting on version conflicts.

this object contains the actual status. It is identical to the response JSON
except for the important addition of the total field. total is the total number
of operations that the _reindex expects to perform. You can estimate the
progress by adding the updated, created, and deleted fields. The request
will finish when their sum is equal to the total field.

With the task id you can look up the task directly. The following example
retrieves information about the task r1A2WoRbTwKZ516z6NEs5A:36619:

GET /_tasks/r1A2WoRbTwKZ516z6NEs5A:36619

The advantage of this API is that it integrates with wait_for_completion=false
to transparently return the status of completed tasks. If the task is completed
and wait_for_completion=false was set, it will return a
results or an error field. The cost of this feature is the document that
wait_for_completion=false creates at .tasks/task/${taskId}. It is up to
you to delete that document.

Just like when setting it on the Reindex API, requests_per_second
can be either -1 to disable throttling or any decimal number
like 1.7 or 12 to throttle to that level. Rethrottling that speeds up the
query takes effect immediately but rethrotting that slows down the query will
take effect on after completing the current batch. This prevents scroll
timeouts.

Setting slices to auto will let Elasticsearch choose the number of slices
to use. This setting will use one slice per shard, up to a certain limit. If
there are multiple source indices, it will choose the number of slices based
on the index with the smallest number of shards.

Adding slices to _reindex just automates the manual process used in the
section above, creating sub-requests which means it has some quirks:

You can see these requests in the Tasks APIs. These
sub-requests are "child" tasks of the task for the request with slices.

Fetching the status of the task for the request with slices only contains
the status of completed slices.

These sub-requests are individually addressable for things like cancelation
and rethrottling.

Rethrottling the request with slices will rethrottle the unfinished
sub-request proportionally.

Canceling the request with slices will cancel each sub-request.

Due to the nature of slices each sub-request won’t get a perfectly even
portion of the documents. All documents will be addressed, but some slices may
be larger than others. Expect larger slices to have a more even distribution.

Parameters like requests_per_second and size on a request with slices
are distributed proportionally to each sub-request. Combine that with the point
above about distribution being uneven and you should conclude that the using
size with slices might not result in exactly size documents being
`_reindex`ed.

Each sub-request gets a slightly different snapshot of the source index,
though these are all taken at approximately the same time.

If slicing automatically, setting slices to auto will choose a reasonable
number for most indices. If slicing manually or otherwise tuning
automatic slicing, use these guidelines.

Query performance is most efficient when the number of slices is equal to the
number of shards in the index. If that number is large (e.g. 500),
choose a lower number as too many slices will hurt performance. Setting
slices higher than the number of shards generally does not improve efficiency
and adds overhead.

Indexing performance scales linearly across available resources with the
number of slices.

Whether query or indexing performance dominates the runtime depends on the
documents being reindexed and cluster resources.

If you have many indices to reindex it is generally better to reindex them
one at a time rather than using a glob pattern to pick up many indices. That
way you can resume the process if there are any errors by removing the
partially completed index and starting over at that index. It also makes
parallelizing the process fairly simple: split the list of indices to reindex
and run each list in parallel.

The new template for the metricbeat-* indices is already loaded into Elasticsearch,
but it applies only to the newly created indices. Painless can be used to reindex
the existing documents and apply the new template.

The script below extracts the date from the index name and creates a new index
with -1 appended. All data from metricbeat-2016.05.31 will be reindexed
into metricbeat-2016.05.31-1.